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@article{195199,
        author = {Mrs.G.Sangeetha and Miss. B.Shanmugavalli and Mr.M.Aravindhan},
        title = {Natural Language Processing Techniques for Automated Legal Document Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {7789-7791},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195199},
        abstract = {Natural Language Processing (NLP) has emerged as a significant field within Artificial Intelligence that enables machines to understand, interpret, and process human language. The legal domain generates vast amounts of textual data in the form of contracts, agreements, affidavits, case judgments, petitions, and legislative documents. Manual review and analysis of such documents is time- consuming, labor-intensive, and prone to human error. Legal professionals often spend considerable time extracting relevant information from lengthy legal texts. This paper presents an automated legal document analysis system using Natural Language Processing techniques to improve efficiency and accuracy in handling legal documents. The proposed system applies text preprocessing, tokenization, stop- word removal, lemmatization, named entity recognition, and machine learning-based classification methods to extract and categorize essential legal information. The system is capable of identifying legal entities such as names, dates, locations, case numbers, and classifying documents into predefined legal categories. By automating document analysis, the system reduces manual effort and enhances accessibility to structured legal information. The proposed approach demonstrates how NLP techniques can significantly transform document management processes within legal institutions.},
        keywords = {Natural Language Processing, Legal Document Analysis, Text Classification, Named Entity Recognition, Machine Learning, Information Extraction.},
        month = {March},
        }